Don`t jump into modelling. First, understand and explore your data! This is common advice for many data scientists. If your data set is messy, building models will not help you to solve your problem. What will happen is “garbage in, garbage out.” In order to build a powerful machine learning
Tag: data preperation
Understanding and interpreting your data set
Reusable data quality enables self-service data preparation
Jim Harris says more reusable data quality processes mean less reliance on IT and higher productivity across the board.